Phenotypes of Polish primary care patients using hierarchical clustering: Exploring the risk of mortality in the LIPIDOGEN2015 study cohort

Eur J Clin Invest. 2024 Oct;54(10):e14261. doi: 10.1111/eci.14261. Epub 2024 Jun 8.

Abstract

Background: Comorbidities in primary care do not occur in isolation but tend to cluster together causing various clinically complex phenotypes. This study aimed to distinguish phenotype clusters and identify the risks of all-cause mortality in primary care.

Methods: The baseline cohort of the LIPIDOGEN2015 sub-study involved 1779 patients recruited by 438 primary care physicians. To identify different phenotype clusters, we used hierarchical clustering and investigated differences between clinical characteristics and mortality between clusters. We then performed causal analyses using causal mediation analysis to explore potential mediators between different clusters and all-cause mortality.

Results: A total of 1756 patients were included (mean age 51.2, SD 13.0; 60.3% female), with a median follow-up of 5.7 years. Three clusters were identified: Cluster 1 (n = 543) was characterised by overweight/obesity (body mass index ≥ 25 kg/m2), older (age ≥ 65 years), more comorbidities; Cluster 2 (n = 459) was characterised by non-overweight/obesity, younger, fewer comorbidities; Cluster 3 (n = 754) was characterised by overweight/obesity, younger, fewer comorbidities. Adjusted Cox regression showed that compared with Cluster 2, Cluster 1 had a significantly higher risk of all-cause mortality (HR 3.87, 95% CI: 1.24-15.91), whereas this was insignificantly different for Cluster 3. Causal mediation analyses showed that decreased protein thiol groups mediated the hazard effect of all-cause mortality in Cluster 1 compared with Cluster 2, but not between Clusters 1 and 3.

Conclusion: Overweight/obesity older patients with more comorbidities had the highest risk of long-term all-cause mortality, and in the young group population overweight/obesity insignificantly increased the risk in the long-term follow-up, providing a basis for stratified phenotypic risk management.

Keywords: ageing; hierarchical clustering; mortality; obesity; primary care; protein thiol groups.

MeSH terms

  • Adult
  • Age Factors
  • Aged
  • Body Mass Index
  • Cause of Death
  • Cluster Analysis
  • Cohort Studies
  • Comorbidity*
  • Female
  • Humans
  • Hypertension / epidemiology
  • Male
  • Middle Aged
  • Mortality
  • Obesity / epidemiology
  • Overweight / epidemiology
  • Phenotype*
  • Poland / epidemiology
  • Primary Health Care* / statistics & numerical data
  • Proportional Hazards Models
  • Risk Factors